Azure Machine Learning Api

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15 major frameworks for machine learning

Machine learning engineers are part of the team that develops products and builds algorithms and ensures that they work reliably, quickly, and on a scale.

Deploying services on Windows Azure Platform

Before introducing, we introduced the three main features of Windows Azure in the Introduction to Windows Azure platform. That's computing, storage, and management. So far, through the previous teaching articles, you have become familiar with the storage capabilities of Windows Azure. Of course, storage is just one of the most basic functions. To give full play to the power of cloud computing, we have to learn how to "compute". Also in the Windows Azure platform profile, we have introduced the three main computational work of Windows Azure ...

Deploying WCF services on Windows Azure

This article will guide you through the first feature: Deploying Services on Windows Azure. Subsequent articles will introduce another two features. In fact, in the Windows Azure Introductory teaching series (I): Creating the first Webrole program, you've tried deploying one of the simplest services: a asp.net web site. Yes, ASP. NET Web site can also be called a service. Now, your ASP.net program is no longer running on your own server, it's running in the clouds. However, Windows ...

How can you build an efficient service-oriented architecture?

"Editor's note" in the famous tweet debate: MicroServices vs. Monolithic, we shared the debate on the microservices of Netflix, Thougtworks and Etsy engineers. After watching the whole debate, perhaps a large majority of people will agree with the service-oriented architecture. In fact, however, MicroServices's implementation is not simple. So how do you build an efficient service-oriented architecture? Here we might as well look to mixrad ...

"Book pick" large data development of the first knowledge of Hadoop

This paper is an excerpt from the book "The Authoritative Guide to Hadoop", published by Tsinghua University Press, which is the author of Tom White, the School of Data Science and engineering, East China Normal University. This book begins with the origins of Hadoop, and integrates theory and practice to introduce Hadoop as an ideal tool for high-performance processing of massive datasets. The book consists of 16 chapters, 3 appendices, covering topics including: Haddoop;mapreduce;hadoop Distributed file system; Hadoop I/O, MapReduce application Open ...

One of the secrets of Microsoft's container technology drawbridge

In building software-defined data centers, VM technology has become increasingly inadequate, container technology as a successor to the emerging slowly. Container technology has a long history, but the emergence of open source technology Docker provides a standard for developers to build portable applications in the form of micro-service. With the maturity of the Docker, the container has been able to meet the portability, automation, choreography and extensibility of the application. As an open source Linux container technology, Docker has been IBM, Google, R ...

Large data processing technology----R analysis of the system PA

With large data being adopted by more enterprises, the compilation and production language of data processing and analysis algorithms have been widely concerned. and unknowingly, open source statistics language R has become a basic technology for large data scientists and developers.   In all programming languages and techniques, popularity has soared. The following is the translation through the integration with the large data processing tools, R provides the depth statistical capability of large datasets, including statistical analysis and data-driven visualization. In industries such as finance, pharmaceuticals, media, and sales, which can directly take decisions from data, R has been applied in depth. ...

To uncover the veil of clouds and to set foot in the clouds.

With the changing cloud world, you want to enter the cloud world in the face of a lot of choices where to go? Here are some examples of the use and testing of well-known cloud services. Before that, of course, we have to know that "cloud" is a service built on hosting your application. auto-scalling-when demand increases, you can automatically get more resources (typically more virtual machines) to respond to requests. This is rarely used in general applications, but it can guarantee that your service will no longer be paralyzed by excessive load, and that it will be icing on the cake only for the purchase you use ...

Interview multiple backup CTO Chen Yuanqiang: Full Open Enterprise Data Cloud eternal life Road

The advent of the 4G era, enterprise data faced with explosive growth, mobile TB; At the same time, human factors, software defects, uncontrollable natural disasters and other security problems occur frequently, how to make the enterprise data security and reliable, low-cost and efficient long-term preservation, has become an urgent concern for any enterprise. Fortunately, the cloud era accompanied by the 4G era, the core advantages of cloud computing: cost-effective, resource allocation, infrastructure flexibility, business smooth switching, bandwidth and storage unlimited expansion features. Multi-backup cloud backup, cloud recovery, cloud archiving and other special ...

VMWare acquisition of SpringSource and the cloud

Many people are concerned about VMWare acquisition of SpringSource this one thing. SpringSource is by far the most popular and fastest-growing management tool, application architecture, application and open source community behind the drivers of change and progress. The acquisition of SpringSource implies that VMWare will become a virtualization vendor in the application and edible markets. This incident has caused us to ponder: cloud computing will be set off on the network storms big thing? For the acquisition of SpringSource, V ...

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